Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1821
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dc.contributor.authorHiremath, S M-
dc.contributor.authorPatra, S K-
dc.contributor.authorMishra, A K-
dc.date.accessioned2013-01-04T10:01:55Z-
dc.date.available2013-01-04T10:01:55Z-
dc.date.issued2012-12-
dc.identifier.citation5th International Conference on Computers and Devices for Communication-CODEC-2012 December 17-19, 2012en
dc.identifier.urihttp://hdl.handle.net/2080/1821-
dc.descriptionCopyright belongs to proceeding Publisheren
dc.description.abstractCognitive radio has emerged as intelligent wireless technology for solving the ever-growing demand of radio spectrum.Cognitive radio is a context aware radio, capable of observing the channel and networks parameters and make autonomously decisions on the best transceiver configuration. Cognitive radio can be made adaptive by utilizing intelligent software techniques. In this paper, we propose Subtractive Clustering with ANFIS based adaptive technique so that it works intelligently to select particular radio configuration. The system considers different time zones and subtractive clustering is used to assist ANFIS in selecting optimum number of rules and membership function. The performance of this is seen to be better than the neural network and ANFIS scheme.en
dc.format.extent279646 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.subjectCognitive radio (CR)en
dc.subjectspectrumholeen
dc.subjectcognition cycleen
dc.subjectANFISen
dc.subjectsubtractive clusteringen
dc.subjectextended schemeen
dc.titleANFIS with Subtractive Clustering-Based Extended Data Rate Prediction for Cognitive Radioen
dc.typeArticleen
Appears in Collections:Conference Papers

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